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UG syllabus R-2017

MA8391 Syllabus Probability and Statistics Regulation 2017 Anna University

MA8391 Syllabus Probability and Statistics Regulation 2017

MA8391 Syllabus Probability and Statistics Regulation 2017 Anna University free download. Probability and Statistics MA8391 Syllabus pdf free download.

UNIT I PROBABILITY AND RANDOM VARIABLES MA8391 Syllabus Probability and Statistics

Probability – The axioms of probability – Conditional probability – Baye‘s theorem – Discrete and continuous random variables – Moments – Moment generating functions – Binomial, Poisson, Geometric, Uniform, Exponential and Normal distributions.

UNIT II TWO – DIMENSIONAL RANDOM VARIABLES MA8391 Syllabus Probability and Statistics

Joint distributions – Marginal and conditional distributions – Covariance – Correlation and linear regression – Transformation of random variables – Central limit theorem (for independent and identically distributed random variables).

UNIT III TESTING OF HYPOTHESIS MA8391 Syllabus Probability and Statistics

Sampling distributions – Estimation of parameters – Statistical hypothesis – Large sample tests based on Normal distribution for single mean and difference of means -Tests based on t, Chi-square and F distributions for mean, variance and proportion – Contingency table (test for independent) – Goodness of fit.

UNIT IV DESIGN OF EXPERIMENTS MA8391 Syllabus Probability and Statistics

One way and Two way classifications – Completely randomized design – Randomized block design – Latin square design – 22 factorial design.

UNIT V STATISTICAL QUALITY CONTROL MA8391 Syllabus

Control charts for measurements (X and R charts) – Control charts for attributes (p, c and np charts) – Tolerance limits – Acceptance sampling.

OBJECTIVES

 This course aims at providing the required skill to apply the statistical tools in engineering problems.
 To introduce the basic concepts of probability and random variables.
 To introduce the basic concepts of two dimensional random variables.
 To acquaint the knowledge of testing of hypothesis for small and large samples which plays
an important role in real life problems.
 To introduce the basic concepts of classifications of design of experiments which plays very important roles in the field of agriculture and statistical quality control.

Subject Name Probability and Statistics
Subject Code MA8391
Regulation 2017
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Syllabus UG syllabus R-2017

IT8602 Syllabus Mobile Communication Regulation 2017 Anna University

IT8602 Syllabus Mobile Communication

IT8602 Syllabus Mobile Communication Regulation 2017 Anna University free download. Mobile Communication Syllabus IT8602 pdf free download.

UNIT I INTRODUCTION IT8602 Syllabus Mobile Communication

Introduction to Mobile Computing – Applications of Mobile Computing- Generations of Mobile Communication Technologies-MAC Protocols – SDMA- TDMA- FDMA- CDMA

UNIT II MOBILE TELECOMMUNICATION SYSTEM IT8602 Syllabus Mobile Communication

GSM – Architecture – Protocols – Connection Establishment – Frequency Allocation – Routing – Mobility Management – Security –GPRS- UMTS- Architecture

UNIT III WIRELESS NETWORKS IT8602 Syllabus Mobile Communication

Wireless LANs and PANs – IEEE 802.11 Standard – Architecture – Services – Blue Tooth- Wi-Fi – WiMAX

UNIT IV MOBILE NETWORK LAYER IT8602 Syllabus Mobile Communication

Mobile IP – DHCP – AdHoc– Proactive and Reactive Routing Protocols – Multicast Routing- Vehicular Ad Hoc networks ( VANET) –MANET Vs VANET – Security

UNIT V MOBILE TRANSPORT AND APPLICATION LAYER IT8602 Syllabus Mobile Communication

Mobile TCP– WAP – Architecture – WDP – WTLS – WTP –WSP – WAE – WTA Architecture – WML

OBJECTIVES:

The student should be made to:
 Understand the basic concepts of mobile computing
 Understand Wireless LAN, Bluetooth and WiFi Technologies
 Be familiar with the network protocol stack
 Learn the basics of mobile telecommunication system
 Be exposed to Ad-Hoc networks

OUTCOMES:

At the end of the course, the student should be able to:
 Explain the basics of mobile telecommunication system
 Illustrate the generations of telecommunication systems in wireless network
 Understand the architecture of Wireless LAN technologies
 Determine the functionality of network layer and Identify a routing protocol for a given Ad hoc networks
 Explain the functionality of Transport and Application layer

Subject name Mobile Communication
Short Name MC
Semester 6
Subject Code IT8602
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

IT8601 Syllabus Computational Intelligence Regulation 2017 Anna University

IT8601 Syllabus Computational Intelligence

IT8601 Syllabus Computational Intelligence Regulation 2017 Anna University free download. Computational Intelligence Syllabus IT8601 pdf free download.

UNIT I INTRODUCTION IT8601 Syllabus Computational Intelligence

Introduction to Artificial Intelligence-Search-Heuristic Search-A* algorithm-Game Playing- Alpha-Beta Pruning-Expert systems-Inference-Rules-Forward Chaining and Backward Chaining- Genetic Algorithms.

UNIT II KNOWLEDGE REPRESENTATION AND REASONING IT8601 Computational Intelligence

Proposition Logic – First Order Predicate Logic – Unification – Forward Chaining -Backward Chaining – Resolution – Knowledge Representation – Ontological Engineering – Categories and Objects – Events – Mental Events and Mental Objects – Reasoning Systems for Categories – Reasoning with Default Information – Prolog Programming.

UNIT III UNCERTAINTY IT8601 Syllabus Computational Intelligence

Non monotonic reasoning-Fuzzy Logic-Fuzzy rules-fuzzy inference-Temporal Logic-Temporal Reasoning-Neural Networks-Neuro-fuzzy Inference.

UNIT IV LEARNING IT8601 Computational Intelligence

Probability basics – Bayes Rule and its Applications – Bayesian Networks – Exact and Approximate Inference in Bayesian Networks – Hidden Markov Models – Forms of Learning – Supervised Learning – Learning Decision Trees – Regression and Classification with Linear Models – Artificial Neural Networks – Nonparametric Models – Support Vector Machines – Statistical Learning – Learning with
Complete Data – Learning with Hidden Variables- The EM Algorithm – Reinforcement Learning

UNIT V INTELLIGENCE AND APPLICATIONS IT8601 Computational Intelligence

Natural language processing-Morphological Analysis-Syntax analysis-Semantic Analysis-AIl applications – Language Models – Information Retrieval – Information Extraction – Machine Translation – Machine Learning – Symbol-Based – Machine Learning: Connectionist – Machine Learning.

Subject name Computational Intelligence
Short Name CI
Semester 6
Subject Code IT8601
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8092 Syllabus Computer Graphics and Multimedia Regulation 2017 Anna University

CS8092 Syllabus Computer Graphics and Multimedia

CS8092 Syllabus Computer Graphics and Multimedia Regulation 2017 Anna University free download. Computer Graphics and Multimedia Syllabus CS8092 pdf free download.

UNIT I ILLUMINATION AND COLOR MODELS CS8092 Syllabus Computer Graphics and Multimedia

Light sources – basic illumination models – halftone patterns and dithering techniques; Properties of light – Standard primaries and chromaticity diagram; Intuitive colour concepts – RGB colour model – YIQ colour model – CMY colour model – HSV colour model – HLS colour model; Colour selection. Output primitives – points and lines, line drawing algorithms, loading the frame buffer, line function; circle and ellipse generating algorithms; Pixel addressing and object geometry, filled area primitives.

UNIT II TWO-DIMENSIONAL GRAPHICS CS8092 Syllabus Computer Graphics and Multimedia

Two dimensional geometric transformations – Matrix representations and homogeneous coordinates, composite transformations; Two dimensional viewing – viewing pipeline, viewing coordinate reference frame; window-to-viewport coordinate transformation, Two dimensional viewing functions; clipping operations – point, line, and polygon clipping algorithms.

UNIT III THREE-DIMENSIONAL GRAPHICS CS8092 Syllabus Computer Graphics and Multimedia

Three dimensional concepts; Three dimensional object representations – Polygon surfaces- Polygon tables- Plane equations – Polygon meshes; Curved Lines and surfaces, Quadratic surfaces; Blobby objects; Spline representations – Bezier curves and surfaces -B-Spline curves and surfaces. TRANSFORMATION AND VIEWING: Three dimensional geometric and modeling transformations – Translation, Rotation, Scaling, composite transformations; Three dimensional viewing – viewing pipeline, viewing coordinates, Projections, Clipping; Visible surface detection methods.

UNIT IV MULTIMEDIA SYSTEM DESIGN & MULTIMEDIA FILE HANDLING CS8092 Syllabus Computer Graphics and Multimedia

Multimedia basics − Multimedia applications − Multimedia system architecture − Evolving technologies for multimedia − Defining objects for multimedia systems − Multimedia data interface standards − Multimedia databases. Compression and decompression − Data and file format standards − Multimedia I/O technologies − Digital voice and audio − Video image and animation − Full motion video − Storage and retrieval technologies.

UNIT V HYPERMEDIA CS8092 Syllabus Computer Graphics and Multimedia

Multimedia authoring and user interface – Hypermedia messaging -Mobile messaging − Hypermedia message component − Creating hypermedia message − Integrated multimedia message standards − Integrated document management − Distributed multimedia systems. CASE STUDY: BLENDER GRAPHICS Blender Fundamentals – Drawing Basic Shapes – Modelling – Shading & Textures

Subject name Computer Graphics and Multimedia
Short Name CGM
Semester 6
Subject Code CS8692
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8091 Syllabus Big Data Analytics Regulation 2017 Anna University

CS8091 Syllabus Big Data Analytics

CS8091 Syllabus Big Data Analytics Regulation 2017 Anna University free download. Big Data Analytics Syllabus CS8091 pdf free download.

UNIT I INTRODUCTION TO BIG DATA CS8091 Syllabus Big Data Analytics

Evolution of Big data – Best Practices for Big data Analytics – Big data characteristics – Validating – The Promotion of the Value of Big Data – Big Data Use Cases- Characteristics of Big Data Applications – Perception and Quantification of Value -Understanding Big Data Storage – A General Overview of High-Performance Architecture – HDFS – MapReduce and YARN – Map Reduce Programming Model

UNIT II CLUSTERING AND CLASSIFICATION CS8091 Syllabus Big Data Analytics

Advanced Analytical Theory and Methods: Overview of Clustering – K-means – Use Cases – Overview of the Method – Determining the Number of Clusters – Diagnostics – Reasons to Choose and Cautions .- Classification: Decision Trees – Overview of a Decision Tree – The General Algorithm – Decision Tree Algorithms – Evaluating a Decision Tree – Decision Trees in R – Naïve Bayes – Bayes‘ Theorem – Naïve Bayes Classifier.

UNIT III ASSOCIATION AND RECOMMENDATION SYSTEM CS8091 Syllabus Big Data Analytics

Advanced Analytical Theory and Methods: Association Rules – Overview – Apriori Algorithm – Evaluation of Candidate Rules – Applications of Association Rules – Finding Association& finding similarity – Recommendation System: Collaborative Recommendation- Content Based Recommendation – Knowledge Based Recommendation- Hybrid Recommendation Approaches.

UNIT IV STREAM MEMORY 9 CS8091 Syllabus Big Data Analytics

Introduction to Streams Concepts – Stream Data Model and Architecture – Stream Computing,
Sampling Data in a Stream – Filtering Streams – Counting Distinct Elements in a Stream – Estimating
moments – Counting oneness in a Window – Decaying Window – Real time Analytics Platform(RTAP) applications – Case Studies – Real Time Sentiment Analysis, Stock Market Predictions. Using Graph Analytics for Big Data: Graph Analytics

UNIT V NOSQL DATA MANAGEMENT FOR BIG DATA AND VISUALIZATION CS8091 Syllabus Big Data Analytics

NoSQL Databases : Schema-less Models‖: Increasing Flexibility for Data Manipulation-Key Value Stores- Document Stores – Tabular Stores – Object Data Stores – Graph Databases Hive – Sharding –-
Hbase – Analyzing big data with twitter – Big data for E-Commerce Big data for blogs – Review of Basic Data Analytic Methods using R.

Subject name Big Data Analytics
Short Name BDS
Semester 6
Subject Code CS8091
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8691 Syllabus Artificial Intelligence Regulation 2017 Anna University

CS8691 Syllabus Artificial Intelligence

CS8691 Syllabus Artificial Intelligence Regulation 2017 Anna University free download. Artificial Intelligence Syllabus CS8691 pdf free download.

UNIT I INTRODUCTION CS8691 Syllabus Artificial Intelligence Regulation

Introduction–Definition – Future of Artificial Intelligence – Characteristics of Intelligent Agents–Typical Intelligent Agents – Problem Solving Approach to Typical AI problems.

UNIT II PROBLEM SOLVING METHODS CS8691 Syllabus Artificial Intelligence Regulation

Problem solving Methods – Search Strategies- Uninformed – Informed – Heuristics – Local Search Algorithms and Optimization Problems – Searching with Partial Observations – Constraint Satisfaction Problems – Constraint Propagation – Backtracking Search – Game Playing – Optimal Decisions in Games – Alpha – Beta Pruning – Stochastic Games

UNIT III KNOWLEDGE REPRESENTATION CS8691 Syllabus Artificial Intelligence Regulation

First Order Predicate Logic – Prolog Programming – Unification – Forward Chaining-Backward Chaining – Resolution – Knowledge Representation – Ontological Engineering-Categories and Objects – Events – Mental Events and Mental Objects – Reasoning Systems for Categories –
Reasoning with Default Information

UNIT IV SOFTWARE AGENTS CS8691 Artificial Intelligence

Architecture for Intelligent Agents – Agent communication – Negotiation and Bargaining –
Argumentation among Agents – Trust and Reputation in Multi-agent systems.

UNIT V APPLICATIONS CS8691 Artificial Intelligence

AI applications – Language Models – Information Retrieval- Information Extraction – Natural Language Processing – Machine Translation – Speech Recognition – Robot – Hardware –
Perception – Planning – Moving

OBJECTIVES:

 To understand the various characteristics of Intelligent agents
 To learn the different search strategies in AI
 To learn to represent knowledge in solving AI problems
 To understand the different ways of designing software agents
 To know about the various applications of AI.

Subject name Artificial Intelligence
Short Name AI
Semester 6
Subject Code CS8691
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8651 Syllabus Internet Programming Regulation 2017 Anna University

CS8651 Syllabus Internet Programming

CS8651 Syllabus Internet Programming Regulation 2017 Anna University free download. Internet Programming Syllabus CS8651 pdf free download.

UNIT I WEBSITE BASICS, HTML 5, CSS 3, WEB 2.0 CS8651 Syllabus Internet Programming

Web Essentials: Clients, Servers and Communication – The Internet – Basic Internet protocols – World wide web – HTTP Request Message – HTTP Response Message – Web Clients – Web Servers – HTML5 – Tables – Lists – Image – HTML5 control elements – Semantic elements – Drag and Drop – Audio – Video controls – CSS3 – Inline, embedded and external style sheets – Rule cascading – Inheritance – Backgrounds – Border Images – Colors – Shadows – Text – Transformations – Transitions – Animations.

UNIT II CLIENT SIDE PROGRAMMING CS8651 Syllabus Internet Programming

Java Script: An introduction to JavaScript–JavaScript DOM Model-Date and Objects,-Regular Expressions- Exception Handling-Validation-Built-in objects-Event Handling- DHTML with JavaScript- JSON introduction – Syntax – Function Files – Http Request – SQL.

UNIT III SERVER SIDE PROGRAMMING CS8651 Syllabus Internet Programming

Servlets: Java Servlet Architecture- Servlet Life Cycle- Form GET and POST actions- Session Handling- Understanding Cookies- Installing and Configuring Apache Tomcat Web Server- DATABASE CONNECTIVITY: JDBC perspectives, JDBC program example – JSP: Understanding Java Server Pages-JSP Standard Tag Library (JSTL)-Creating HTML forms by embedding JSP code.

UNIT IV PHP and XML CS8651 Syllabus Internet Programming

An introduction to PHP: PHP- Using PHP- Variables- Program control- Built-in functions- Form Validation- Regular Expressions – File handling – Cookies – Connecting to Database. XML: Basic XML- Document Type Definition- XML Schema DOM and Presenting XML, XML Parsers and Validation, XSL and XSLT Transformation, News Feed (RSS and ATOM).

UNIT V INTRODUCTION TO AJAX and WEB SERVICES CS8651 Syllabus Internet Programming

AJAX: Ajax Client Server Architecture-XML Http Request Object-Call Back Methods; Web Services: Introduction- Java web services Basics – Creating, Publishing, Testing and Describing a Web services (WSDL)-Consuming a web service, Database Driven web service from an application –SOAP.

Subject name Internet Programming
Short Name IP
Semester 6
Subject Code CS8651
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8603 Syllabus Distributed Systems Regulation 2017 Anna University

CS8603 Syllabus Distributed Systems

CS8603 Syllabus Distributed Systems Regulation 2017 Anna University free download. Distributed Systems Syllabus CS8603 pdf free download.

UNIT I INTRODUCTION 9 CS8603 Syllabus Distributed Systems

Introduction: Definition –Relation to computer system components –Motivation –Relation to parallel systems – Message-passing systems versus shared memory systems –Primitives for distributed communication –Synchronous versus asynchronous executions –Design issues and challenges. A model of distributed computations: A distributed program –A model of distributed executions –Models of communication networks –Global state – Cuts –Past and future cones of an event –Models of process communications. Logical Time: A framework for a system of logical clocks –Scalar time –Vector time – Physical clock synchronization: NTP.

UNIT II MESSAGE ORDERING & SNAPSHOTS CS8603 Syllabus Distributed Systems

Message ordering and group communication: Message ordering paradigms –Asynchronous execution with synchronous communication –Synchronous program order on an asynchronous system –Group communication – Causal order (CO) – Total order. Global state and snapshot recording algorithms: Introduction –System model and definitions –Snapshot algorithms for FIFO channels

UNIT III DISTRIBUTED MUTEX & DEADLOCK CS8603 Syllabus Distributed Systems

Distributed mutual exclusion algorithms: Introduction – Preliminaries – Lamport‘s algorithm – Ricart-Agrawala algorithm – Maekawa‘s algorithm – Suzuki–Kasami‘s broadcast algorithm. Deadlock detection in distributed systems: Introduction – System model – Preliminaries – Models of deadlocks – Knapp‘s classification – Algorithms for the single resource model, the AND model and the OR model.

UNIT IV RECOVERY & CONSENSUS CS8603 Syllabus Distributed Systems

Checkpointing and rollback recovery: Introduction – Background and definitions – Issues in failure recovery – Checkpoint-based recovery – Log-based rollback recovery – Coordinated checkpointing algorithm – Algorithm for asynchronous checkpointing and recovery. Consensus and agreement algorithms: Problem definition – Overview of results – Agreement in a failure –
free system – Agreement in synchronous systems with failures.

UNIT V P2P & DISTRIBUTED SHARED MEMORY 9 CS8603 Syllabus Distributed Systems

Peer-to-peer computing and overlay graphs: Introduction – Data indexing and overlays – Chord – Content addressable networks – Tapestry. Distributed shared memory: Abstraction and advantages – Memory consistency models –Shared memory Mutual Exclusion.

Subject name Distributed Systems
Short Name DS
Semester 6
Subject Code CS8603
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8602 Syllabus Compiler Design Regulation 2017 Anna University

CS8602 Syllabus Compiler Design

CS8602 Syllabus Compiler Design Regulation 2017 Anna University free download. Compiler Design Syllabus CS8602 pdf free download.

UNIT I INTRODUCTION TO COMPILERS 9 CS8602 Syllabus Compiler Design

Structure of a compiler – Lexical Analysis – Role of Lexical Analyzer – Input Buffering – Specification of Tokens – Recognition of Tokens – Lex – Finite Automata – Regular Expressions to Automata – Minimizing DFA.

UNIT II SYNTAX ANALYSIS 12 CS8602 Syllabus Compiler Design

Role of Parser – Grammars – Error Handling – Context-free grammars – Writing a grammar – Top Down Parsing – General Strategies Recursive Descent Parser Predictive Parser-LL(1) Parser-Shift Reduce Parser-LR Parser-LR (0)Item Construction of SLR Parsing Table -Introduction to LALR Parser – Error Handling and Recovery in Syntax Analyzer-YACC.

UNIT III INTERMEDIATE CODE GENERATION 8 CS8602 Syllabus Compiler Design

Syntax Directed Definitions, Evaluation Orders for Syntax Directed Definitions, Intermediate Languages: Syntax Tree, Three Address Code, Types and Declarations, Translation of Expressions, Type Checking.

UNIT IV RUN-TIME ENVIRONMENT AND CODE GENERATION 8 CS8602 Syllabus Compiler Design

Storage Organization, Stack Allocation Space, Access to Non-local Data on the Stack, Heap Management – Issues in Code Generation – Design of a simple Code Generator.

UNIT V CODE OPTIMIZATION 8 CS8602 Syllabus Compiler Design

Principal Sources of Optimization – Peep-hole optimization – DAG- Optimization of Basic Blocks-Global Data Flow Analysis – Efficient Data Flow Algorithm.

LIST OF EXPERIMENTS:

1. Develop a lexical analyzer to recognize a few patterns in C. (Ex. identifiers, constants, comments, operators etc.). Create a symbol table, while recognizing identifiers.
2. Implement a Lexical Analyzer using Lex Tool
3. Implement an Arithmetic Calculator using LEX and YACC
4. Generate three address code for a simple program using LEX and YACC.
5. Implement simple code optimization techniques (Constant folding, Strength reduction and Algebraic transformation)
6. Implement back-end of the compiler for which the three address code is given as input and the 8086 assembly language code is produced as output.

Subject name Compiler Design
Short Name CD
Semester 6
Subject Code CS8602
Regulation 2017 regulation

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Syllabus UG syllabus R-2017

CS8601 Syllabus Mobile Computing Regulation 2017 Anna University

CS8601 Syllabus Mobile Computing

CS8601 Syllabus Mobile Computing Regulation 2017 Anna University free download. Mobile Computing Syllabus CS8601 pdf free download.

UNIT I INTRODUCTION CS8601 Mobile Computing

Introduction to Mobile Computing – Applications of Mobile Computing- Generations of Mobile Communication Technologies- Multiplexing – Spread spectrum -MAC Protocols – SDMA- TDMA- FDMA- CDMA

UNIT II MOBILE TELECOMMUNICATION SYSTEM CS8601 Syllabus Mobile Computing

Introduction to Cellular Systems – GSM – Services & Architecture – Protocols – Connection Establishment – Frequency Allocation – Routing – Mobility Management – Security – GPRS- UMTS – Architecture – Handover – Security

UNIT III MOBILE NETWORK LAYER CS8601 Syllabus Mobile Computing

Mobile IP – DHCP – AdHoc– Proactive protocol-DSDV, Reactive Routing Protocols – DSR, AODV , Hybrid routing –ZRP, Multicast Routing- ODMRP, Vehicular Ad Hoc networks ( VANET) –MANET Vs VANET – Security.

UNIT IV MOBILE TRANSPORT AND APPLICATION LAYER CS8601 Syllabus Mobile Computing

Mobile TCP– WAP – Architecture – WDP – WTLS – WTP –WSP – WAE – WTA Architecture – WML

UNIT V MOBILE PLATFORMS AND APPLICATIONS CS8601 Syllabus Mobile Computing

Mobile Device Operating Systems – Special Constraints & Requirements – Commercial Mobile Operating Systems – Software Development Kit: iOS, Android, BlackBerry, Windows Phone – MCommerce – Structure – Pros & Cons – Mobile Payment System – Security Issues

OBJECTIVES: CS8601 Syllabus Mobile Computing

 To understand the basic concepts of mobile computing.
 To learn the basics of mobile telecommunication system .
 To be familiar with the network layer protocols and Ad-Hoc networks.
 To know the basis of transport and application layer protocols.
 To gain knowledge about different mobile platforms and application development.

Subject name Mobile Computing
Short Name MC
Semester 6
Subject Code CS8601
Regulation 2017 regulation

CS8601 Syllabus Mobile Computing Click Here To Download

CS8601 Mobile Computing Notes


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